Traditional IT infrastructures were made up of the proverbial technology silos. They included experts in networking, storage, systems administration, and software. But much of that has changed over the past decade or so as virtualization has become a prominent technology tying networks and servers together.
Today's virtual environments can be likened to the ubiquitous smartphone. Smartphone users generally don't concern themselves with issues such as storage or systems management; everything they need is just an app. Similarly, storage management on converged infrastructure systems are provisioned essentially as an app as well.
Generally speaking, there are two approaches companies can take to building a converged infrastructure. One is a hardware-focused, building-block approach, sometimes referred to as having a converged architecture. The second approach is a hyper-converged architecture where all the technology is essentially software defined.
In a converged architecture, each of the components in the building block is a discrete component that can be used for its intended purpose—the server can be separated and used as a server, just as the storage can be separated and used as functional storage. By contrast, in a hyper-converged architecture—the technology being software defined—in essence the building blocks are all integrated and cannot be broken out into separate components.
When a company desires to implement server or desktop virtualization, in an early generation typical non-converged approach, physical servers would be set up to run a virtualization hypervisor the role of which is to manage each of the virtual machines (VMs) created on that server. The data storage for those physical and virtual machines would be provided by direct attached storage (DAS), network attached storage (NAS) or a storage area network (SAN).
By contrast, in a converged architecture, the storage is attached directly to the physical servers. Flash storage generally is used for high-performance applications and for caching storage from the attached disk-based storage. With hyper-converged architectures, the infrastructure includes a storage controller function running as a service on each node in the cluster to improve scalability and resilience. The storage logic controller, which normally is part of SAN hardware, may for example serve as a software service attached to each VM at the hypervisor level. This software defined storage approach takes all of the local storage across the cluster and configures it as a single storage pool. Data that needs to be kept local for the fastest response could be stored locally, while data that is used less frequently can be stored on one of the servers that might have spare capacity.
Like traditional infrastructures, the cost of a hyper-converged infrastructure can vary dramatically. In addition to licensing costs associated with the particular virtualization technology (hypervisor) deployed, there are many costs involved in configuring the software for use in a given environment.
“Software defined” allows programmatic control of the corporate infrastructure as a company moves forward. For this reason, hyper-converged infrastructures are becoming a best IT planning approach when a company's ability to address automation, orchestration, and control more quickly and effectively to account for increased needs to expand the overall computing environment is critical.
Hyper-converged infrastructures allow an IT operator to be able to easily reconfigure the infrastructure at the hypervisor level to respond to changes in configuration more quickly than was possible in the past, providing a very cost-effective long term solution, at least for those companies that are designing an infrastructure budgeted for future expansion.
Expansion often involves rolling out x86-based servers in a building-block chassis to allow a company to easily expand the computing environment with new hardware. With hyper-converged architectures, a downstream savings is realized by having budgeted for expansion in the form of lower support and maintenance costs. With that said, because the software is a key component of a hyper-converged infrastructure, integration of new hardware to an existing infrastructure needs to be carefully thought through in advance so that the expansion goals and objectives—which often involve optimization of resources for mission critical workloads—are achieved.
With hyper-convergence, there is an overall convergence trend whereby more and more distributed hardware components are being combined together making it possible to pack an entire datacenter into an appliance form factor.
Also, hyper-convergence being built around virtualization technology, another name of which is hypervisor, in essence what happens is that the virtual aspects of an infrastructure are brought together with the physical, resulting in a single solution. Many hyper-converged solutions include software hooks which allow for the hypervisor and related management tools to be easily integrated when configuring a hyper-converged system. In some cases, the entire virtualization layer can be embedded into the system itself. In this way, aspects such as automated management, system clustering and hardware failure recovery, virtualization management, resource provisioning, and VM failover can be handled by the virtualization layer once setup and running.
With a hyper-converged infrastructure, all desired applications that a company needs to run across a common computing environment will behave as a single, comprehensive system. Servers, storage and virtualization stack are not only bundled together, but are completely integrated and transparent to the administrator.
In this regard, hyper-convergence has extended the trend of datacenter convergence beyond hardware components to include integration of the hypervisor itself.
A converged infrastructure can be configured in a single rack or even expanded for scalable clouds.
From a load balancing standpoint, in a physical server environment, each workload requires a compatible server configured and tuned to optimize results for that particular application. From the perspective of optimizing each workload, this makes sense because you want to build the application on the best possible platform to achieve a best result. Keeping the physical layout and configuration for each particular machine—and ordering, building and implementing them on a custom basis for each workload—creates a tremendous amount of variability and complexity across a server virtualization storage environment.
Buying separate software, servers, storage and networking, and then attempting to make it all fit together is akin to buying a car by ordering an engine from one manufacturer, the chassis from another and the wheels, seats and body from additional vendors. While theoretically it might be possible to get better results than trusting the combination a single vendor recommends, the likelihood of such a result is extremely low. With improvements in the ability of industry-standard x86 components to handle demanding workloads, and the standardization of components from one vendor to another, many IT architects are realizing that there's more value in making things consistent and eliminating variability, rather than striving for the absolute best architecture for each individual workload.
Converged storage options are a natural outcome of this line of thinking. The rise of virtual servers has had a homogenizing effect on IT requirements. Today, you just need to know your workload is compatible with virtualization, and that your server is compatible with your virtual server technology, and that's how you build the server. The specific requirements of each application in the virtual server environment become, to some extent, less important.
As organizations rely on virtual server technology for a bigger percentage of the workloads they run, server virtualization storage needs need to be provided by customized configurations that differ by workload.
Hyper-converged architectures act as a homogenizing factor, removing variability and interoperability from the equation. When organizations standardize on a virtual server technology, and run a majority of their production workloads in a hyper-converged environment, this allows for a much higher level of infrastructure consistency from workload to workload.
Appropriate provisioning of resources between applications is a key aspect of hyper-converged systems. Thin provisioning is an example feature that's especially helpful in virtual server environments. Thin provisioning allows every server to get the same allocation process and the appearance of the same amount of capacity, but the physical space isn't reserved for that server until it actually needs it. This gives the environment the best of both worlds—the process is consistent and can be highly automated, but the storage capacity consumption is dramatically reduced.
Disaster Recovery
In a hyper-converged system, all VMs run on the system. In the event of a disaster, the VMs may be unable to connect to the system to access mission-critical information. One data recovery approach involves having virtual machines run in the cloud while a business gets back on its feet. Many organizations have begun basing their disaster recovery plans completely around the cloud.
Virtual machines run in the cloud until data center issues can be resolved. The problem is getting virtual machines to function in the cloud. Another problem is being able to seamlessly restore access to real-time data which may not have been backed up to the cloud immediately before the system went down due to a disaster.
These problems have created a need for solutions capable of providing mission critical access to data to one or more key personnel in the event of a major disaster when access to an established, hyper-converged infrastructure is impossible.